Abstract
BP neural network optimized by standard genetic algorithm is hard to meet the balance between global search capability with local search capability. Therefore, the decay parameters genetic algorithms were presented to improve the convergence rate and accuracy. The results of this approach were compared with that of the standard genetic algorithm as well as the improved genetic algorithm by MATLAB simulation software. The simulation results show that the decay parameter genetic algorithm has better accuracy and robustness than the standard genetic algorithm, and greatly gives consideration to both the global search ability and the ability of local search. As a result, the precision and speed on the system fault diagnosis are dramatically improved.
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